Book Image

Learning Python

By : Fabrizio Romano
Book Image

Learning Python

By: Fabrizio Romano

Overview of this book

Learning Python has a dynamic and varied nature. It reads easily and lays a good foundation for those who are interested in digging deeper. It has a practical and example-oriented approach through which both the introductory and the advanced topics are explained. Starting with the fundamentals of programming and Python, it ends by exploring very different topics, like GUIs, web apps and data science. The book takes you all the way to creating a fully fledged application. The book begins by exploring the essentials of programming, data structures and teaches you how to manipulate them. It then moves on to controlling the flow of a program and writing reusable and error proof code. You will then explore different programming paradigms that will allow you to find the best approach to any situation, and also learn how to perform performance optimization as well as effective debugging. Throughout, the book steers you through the various types of applications, and it concludes with a complete mini website built upon all the concepts that you learned.
Table of Contents (20 chapters)
Learning Python
About the Author
About the Reviewers

Dealing with data

Typically, when you deal with data, this is the path you go through: you fetch it, you clean and manipulate it, then you inspect it and present results as values, spreadsheets, graphs, and so on. I want you to be in charge of all three steps of the process without having any external dependency on a data provider, so we're going to do the following:

  1. We're going to create the data, simulating the fact that it comes in a format which is not perfect or ready to be worked on.

  2. We're going to clean it and feed it to the main tool we'll use in the project: DataFrame of pandas.

  3. We're going to manipulate the data in the DataFrame.

  4. We're going to save the DataFrame to a file in different formats.

  5. Finally, we're going to inspect the data and get some results out of it.

Setting up the notebook

First things first, we need to set up the notebook. This means imports and a bit of configuration.


import json
import calendar
import random
from datetime import date, timedelta

import faker